Supporting Thyroid Cancer Diagnosis based on Cell Classification over Microscopic Images

The study of illness at the cellular level is known as cytology and is frequently used as a cancer screening technique. Thyroid cytology is a discipline of pathology that focuses on the diagnosis of thyroid disorders and lesions. When discussing thyroid gland tumor categorization, dissolving samples with and without “papillary thyroid carcinoma-like” nuclei is a process that takes a long time for a doctor, and the results depend on the doctor’s experience. Therefore, the research and application of artificial intelligence, in particular, methods of classifying cells based on microscopic images, are currently of great interest to assist doctors in the diagnostic process. In this paper, we develop a deep learning model named Inception-v3 for cancer cell classification to support the diagnostic process.

I. Introduction

A cell is the smallest unit in an organism. An organism is a living creature made up of one or more cells, such as bacteria or humans. Hence the fundamental components of all living things. Tissues are made up of several cells of the same kind that are interconnected and execute a common function; organs such as the stomach, heart, or brain are made up of multiple organs, and organ systems are made up of multiple organs (such as the digestive system, circulatory system, or nervous system).